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Issue in the gridding correction function? #14
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I agree it's an issue but I don't agree totally with your change.
[grdsf.f.txt](https://github.com/SKA-ScienceDataProcessor/algorithm-reference-library/files/1951338/grdsf.f.txt)
I've attached the Fortran file from which this python version was derived. Reading from that I think the lines should be:part[(nu >= 0.0) & (nu < 0.75)] = 0 part[(nu >= 0.75) & (nu <= 1.0)] = 1 nuend[(nu >= 0.0) & (nu <= 0.75)] = 0.75 nuend[(nu > 0.75) & (nu <= 1.0)] = 1.0Can you check this line of derivation?
How did this manifest itself? I'm impressed that you found it.
Cheers,
TimScratch that. It should be:
part[(nu >= 0.0) & (nu < 0.75)] = 0 part[(nu >= 0.75) & (nu <= 1.0)] = 1 nuend[(nu >= 0.0) & (nu < 0.75)] = 0.75 nuend[(nu >= 0.75) & (nu <= 1.0)] = 1.0i.e. the selections must be the same for part and nun.
I'm working on W-Projection (implementation based on your paper) for the Slow Transients Pipeline (first on Python and then on C++ implementation).
I found this issue while debugging W-projection implementation for the STP and inspecting the generated matrices. We had an idea to speedup W-projection implementation using Hankel transform. While it appeared to work using a Gaussian AA-kernel, we observed that for PSWF some artifacts arise close to the image borders. I found this issue while inspecting the correction gridding function values but this was not the cause for the artifacts. However, this issue may affect some image border samples when performing the gridding correction step. Thanks for your correction. I'm not aware of PSWF implementation details.- Interesting! Why would you want to do w projection for a snapshot image? The quicker approach would be to do a 2D FFT, which will result in a distorted image but you can either search in that and correct the coordinates of any detected source or reproject the entire image to the correct coordinates and then search.…On 26 Apr 2018, at 3:06 pm, Luís Lucas ***@***.***> wrote: I'm working on W-Projection (implementation based on your paper) for the Slow Transients Pipeline (first on Python and then on C++ implementation). I found this issue while debugging W-projection implementation for the STP and inspecting the generated matrices. We had an idea to speedup W-projection implementation using Hankel transform. While it appeared to work using a Gaussian AA-kernel, we observed that for PSWF some artifacts arise close to the image borders. I found this issue while inspecting the correction gridding function values but this was not the cause for the artifacts. However, this issue may affect some image border samples when performing the gridding correction step. Thanks for your correction. I'm not aware of PSWF implementation details. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#14 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ADv3XdbNzkjBJ0JNRzre66Z2YN6u9jS0ks5tsdRJgaJpZM4TlIX2>.
We're seeing if we can be quicker than reprojection :-)
- Let me know!…On 26 Apr 2018, at 3:15 pm, as595 ***@***.***> wrote: We're seeing if we can be quicker than reprojection :-) — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#14 (comment)>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ADv3XUP9_6qLVqN2Bq0J-1UyBQYB0E70ks5tsdZ4gaJpZM4TlIX2>.
Also - there are a variety of different integration lengths requested for the STP, so a w-correction of some sort may be required anyway.
Thanks Anna.
Tim, I tested your correction. I observe that fixing nu=0.75 results in a quite small difference for the value in this position. But the selections are consistent now. Thanks.- added a commit that references this issue
on Apr 26, 2018 - added a commit that references this issue
on Nov 28, 2018 Now complete.
Hi,
While using your PSWF code for the Slow Transients Pipeline, I observed that the first element of the 1D gridding correction function (at position nu=-1) is different than the expected:
In this image it is about 0.0212, but I would expect a smaller value than next one of 0.007, as it tends to decrease for smaller indexes.
Apparently this can be fixed by changing the following lines of grdsf function:
to:
Do you agree this is an issue?
Thanks.